The present invention relates to linear sensors, as well as calibration and use of such sensors. The invention is applicable to systems comprising one or more linear sensors.
Sensors are employed in a multitude of applications throughout a variety of industries. Sensors can be used to detect many different properties. For example, it is well known to use sensors for detecting pressure, strain, temperature, torque, and many other properties. In most industrial applications, sensors are also referred to as transducers.
Whether a sensor is linear depends on how its output (e.g., electrical signal such as voltage) correlates with the measured input (e.g., pressure, strain, temperature, torque, et cetera). If the relationship between input and output is essentially linear when operating the sensor at constant temperature, the sensor is then understood to be linear. If not linear, the sensor is characterized according to what other type of relationship (e.g., exponential) exists between the sensor's input and output.
In some applications, one or more sensors can be integrated within a larger unit.
For example, mechatronic units provide mechanical and electronic (e.g., microprocessor and/or memory) components within one integral unit. Mechatronic units can be rather small, encompassing no more than a sensor and an electronic component which can, for example, store a calibration algorithm for the individual sensor. Mechatronic units in industrial applications, however, often include a multitude of components operating together to perform a discrete function.
One class of mechatronic unit widely used in industry is electrohydraulic in nature, integrating hydraulic and electronic components within one integral unit. Many electrohydraulic units are known to include one or more sensors to facilitate desired and reliable operation of the unit. For example, solenoid operated pressure control valves are electrohydraulic units in which sensors are commonly utilized. In applications of this type, sensors can be utilized, for example, to determine and relay to an electronic component (such as a pressure controller) pressure output from and/or input to such a valve. Relaying pressure readings in this manner can, for instance, assist an electronic pressure controller in adjusting the hydraulic components of the valve during operation in order to obtain a desired pressure output.
Units comprising solenoid operated pressure control valves have found applicability in, for example, applications for controlling the flow of hydraulic fluid in automatic transmissions for motor vehicles. In automatic transmissions of this type, shifting of transmission speed ratios is controlled by an electronic controller that provides an electrical signal to the solenoid operated valve, which in turn provides a fluid pressure signal to a pressure responsive actuator for effecting a desired transmission speed ratio change.
Accuracy and reliability of mechatronic units (whether they be relatively small or larger, such as automatic transmission systems employing solenoid operated pressure control valves), however, are often predicated on calibration of sensors and other components within the system. Known mechatronic units comprising a sensor calibration algorithm in the electronic component typically rely upon sensor calibration that is determined on a sensor-by-sensor basis prior to the assembly of the sensors into a complete mechatronic unit.
Yet, the calibration of sensors in assembled mechatronic units (e.g., solenoid operated pressure control valve systems) and maintenance of sensor calibration during operation has proven challenging. As is known by those skilled in the sensor art, the output of sensors at pre-assembly often varies from the sensor output obtained after assembly into a mechatronic unit. The pre-assembly sensor output also may vary from sensor output under varying operating conditions.
For example, environmental variations such as temperature changes and exposure to fluid contaminants, as well as viscosity fluctuations, can impact sensor output. FIG. 1 illustrates variation in individual sensor output based on temperature variations during operation. FIG. 1 shows the relationship between sensor output and input at three different temperatures (i.e., Temp. A, Temp. B, and Temp. C). Such variations observed in sensor output at varying temperatures can detrimentally impact continued accuracy of systems relying on precise output of sensors during operation. Conventional sensor calibration algorithms, if used, often do not factor in these environmental variations.
Still other post-assembly variations, such as those caused by sensor packaging and attachment can also influence sensor output measurements. For example, the methods for packaging and attachment of a sensor to a substrate can influence sensor outputs. In addition, the materials used for sensor packaging and attachment (e.g., type of the substrate material, such as ceramic or “FR4”) can also influence sensor outputs after its assembly into a final product.
Furthermore, when more than one sensor is employed within a mechatronic unit or combination of units, sensor variance between parts imparted during normal manufacturing processes can further complicate accurate calibration of the mechatronic units during operation. For example, FIG. 2 illustrates variations in sensor output based on part-to-part variations created during sensor manufacture. Illustrated therein is the relationship between sensor output of three similar sensors obtained from different manufacturing lots (i.e., Part A, Part B, and Part C) and sensor input. The data represented in FIG. 2 is obtained while operating the three different sensors under the same operating conditions (e.g., at the same temperature). Conventional calibration algorithms typically are not universally applicable to various types of sensors. Further, conventional calibration algorithms do not account for individual variances (e.g., those imparted during normal manufacturing processes) within each class of sensor.
Factoring in environmental and part-to-part variations, desired sensor output can vary by up to approximately 50% from actual sensor output in assembled mechatronic units. Not surprisingly, such large deviations in accuracy are often problematic. Thus, there is a need for improvement in techniques used to calibrate units employing linear sensors and to maintain accurate calibration thereof during operation.
While certain attempts have been made to minimize deviations in the accuracies of sensor output, those attempts are not without their drawbacks. Notably, many of these techniques require additional hardware and/or burdensome individual testing of each sensor.
For example, one conventional technique for minimizing deviations in the accuracy of sensor output involves individually calibrating each sensor after packaging. This individual calibration step is followed by separate signal conditioning and amplification of the sensor in order to facilitate obtainment of linear output under all operating conditions. Yet, such a technique requires manual setup by an end user using a paper “calibration sheet.” As anticipated, that manual process can be very inefficient, particularly when utilizing a combination of multiple sensors within a larger mechatronic unit.
Alternatively, instead of requiring a paper calibration sheet, an individual sensor can be coupled to an application specific integrated circuit (ASIC) having an individual sensor calibration algorithm encoded within. Requiring the use of an ASIC in this manner, however, is very costly and adds often undesired physical bulk to each individual sensor and hence the unit within which it is placed for operation.
Another technique for minimizing deviations in the accuracy of sensor output involves physical “trimming” of packaged sensors such that each individual sensor provides the same output at all operating conditions. Again, this technique has its drawbacks, one of which is the decrease in process efficiency associated with the trimming process. Another drawback is that signal conditioning is often required with this technique, which has the effect of decreasing overall process efficiency.
Further techniques for minimizing deviations in sensor accuracy after assembly and during operation are desirable. In particular, improved calibration methods are needed, especially those that promote overall process efficiency.